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Using Results From Replicated Studies to Estimate Linear Models

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  • Betsy Jane Becker

Abstract

This article outlines analyses for the results of a series of studies examining intercorrelations among a set of p + 1 variables. A test of whether a common population correlation matrix underlies the set of empirical results is given. Methods are presented for estimating either a pooled or average correlation matrix, depending on whether the studies appear to arise from a single population. A random effects model provides the basis for estimation and testing when the series of correlation matrices may not share a common population matrix. Finally, I show how a pooled correlation matrix (or average matrix) can be used to estimate the standardized coefficients of a regression model for variables measured in the series of studies. Data from a synthesis of relationships among mathematical, verbal, and spatial ability measures illustrate the procedures.

Suggested Citation

  • Betsy Jane Becker, 1992. "Using Results From Replicated Studies to Estimate Linear Models," Journal of Educational and Behavioral Statistics, , vol. 17(4), pages 341-362, December.
    • Handle: RePEc:sae:jedbes:v:17:y:1992:i:4:p:341-362
    DOI: 10.3102/10769986017004341
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    Cited by:

    1. Piotr Tarka, 2018. "An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 313-354, January.
    2. Jerome Geyer-Klingeberg & Markus Hang & Andreas W. Rathgeber & Stefan Stöckl & Matthias Walter, 2018. "What do we really know about corporate hedging? A meta-analytical study," Business Research, Springer;German Academic Association for Business Research, vol. 11(1), pages 1-31, February.

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